Triple
T10654638
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aloísio Lorscheider |
E251056
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Lorscheider
Lorscheider is a German-origin surname notably borne by Brazilian Cardinal Aloísio Lorscheider.
|
E877415
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Lorscheider | Statement: [Aloísio Lorscheider, familyName, Lorscheider]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lorscheider Context triple: [Aloísio Lorscheider, familyName, Lorscheider]
-
A.
Loerzer
Loerzer is the surname of Bruno Loerzer, a notable German First World War flying ace and later Luftwaffe general.
-
B.
Hufstedler
Hufstedler is the surname of Shirley Hufstedler, a prominent American judge and the first U.S. Secretary of Education.
-
C.
Oberhauser
Oberhauser is a German-language surname borne by various notable individuals across fields such as sports, the arts, and public life.
-
D.
Hollander
Hollander is a surname most prominently associated with English actor Tom Hollander, known for his versatile roles in film, television, and theatre.
-
E.
Wolthusen
Wolthusen is a district of the seaport city of Emden in Lower Saxony, Germany, known for its residential character and proximity to the Ems estuary.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Lorscheider Triple: [Aloísio Lorscheider, familyName, Lorscheider]
Generated description
Lorscheider is a German-origin surname notably borne by Brazilian Cardinal Aloísio Lorscheider.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lorscheider Target entity description: Lorscheider is a German-origin surname notably borne by Brazilian Cardinal Aloísio Lorscheider.
-
A.
Loerzer
Loerzer is the surname of Bruno Loerzer, a notable German First World War flying ace and later Luftwaffe general.
-
B.
Hufstedler
Hufstedler is the surname of Shirley Hufstedler, a prominent American judge and the first U.S. Secretary of Education.
-
C.
Oberhauser
Oberhauser is a German-language surname borne by various notable individuals across fields such as sports, the arts, and public life.
-
D.
Hollander
Hollander is a surname most prominently associated with English actor Tom Hollander, known for his versatile roles in film, television, and theatre.
-
E.
Wolthusen
Wolthusen is a district of the seaport city of Emden in Lower Saxony, Germany, known for its residential character and proximity to the Ems estuary.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d6aa5a4c4881908f39be6efe5981e5 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6dff94c188190b1a822c3720d18b7 |
completed | April 8, 2026, 11:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d97a71fac48190a6d7c99ebc5aad0a |
completed | April 10, 2026, 10:32 p.m. |
| NEDg | Description generation | batch_69d97cc2b66c8190909a23927fbe3af5 |
completed | April 10, 2026, 10:42 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d97e13913081908dd1fb60fa44db05 |
completed | April 10, 2026, 10:47 p.m. |
Created at: April 8, 2026, 9:06 p.m.